Skeletal muscle is associated with exercise tolerance evaluated by cardiopulmonary exercise testing in Japanese patients with chronic obstructive ...
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OPEN Skeletal muscle is associated
with exercise tolerance evaluated
by cardiopulmonary exercise
testing in Japanese patients
with chronic obstructive pulmonary
disease
Hiroki Tashiro1*, Koichiro Takahashi1, Masahide Tanaka1, Hironori Sadamatsu1,
Yuki Kurihara1, Ryo Tajiri2, Ayako Takamori2, Hiroyuki Naotsuka3, Hiroki Imaizumi3,
Shinya Kimura1 & Naoko Sueoka‑Aragane1
Decreasing exercise tolerance is one of the key features related to a poor prognosis in patients with
chronic obstructive pulmonary disease (COPD). Cardiopulmonary exercise testing (CPET) is useful for
evaluating exercise tolerance. The present study was performed to clarify the correlation between
exercise tolerance and clinical parameters, focusing especially on the cross-sectional area (CSA)
of skeletal muscle. The present study investigated 69 patients with COPD who underwent CPET.
The correlations between oxygen uptake ( VO ˙ 2) at peak exercise and clinical parameters of COPD,
including skeletal muscle area measured using single-section axial computed tomography (CT), were
evaluated. The COPD assessment test score (ρ = − 0.35, p = 0.02) was weakly correlated with VO ˙ 2
at peak exercise. In addition, forced expiratory volume in one second (FEV1) (ρ = 0.39, p = 0.0009),
FEV1/forced vital capacity (ρ = 0.33, p = 0.006), and the CSA of the pectoralis muscles (PMs) (ρ = 0.36,
p = 0.007) and erector spinae muscles (ECMs) (ρ = 0.39, p = 0.003) were correlated with VO˙ 2 at peak
exercise. Multivariate analysis adjusted by age and FEV1 indicated that PMCSA was weakly correlated
after adjustment (β value [95% confidence interval] 0.175 [0.03–0.319], p = 0.02). In addition, ECMCSA
tended to be correlated, but not significantly after adjustment (0.192 [− 0.001–0.385] p = 0.052). The
COPD assessment test, FEV1, FEV1/FVC, PMCSA, and ECMCSA were significantly correlated with VO ˙ 2 at
peak exercise.
Chronic pulmonary obstructive disease (COPD) is a common respiratory disease, with a reported global preva-
lence of 251 million c ases1, and it is considered a life-threatening disease with decreasing pulmonary function
and airflow l imitation2.
Recently, factors related to a poor prognosis of COPD patients, including mortality and exacerbations, are
becoming understood as evidence increases. For example, low-level physical activity, percent predicted forced
expiratory volume in one second (%FEV1), 6-min walk distance, body mass index (BMI), and a high frequency
of exacerbations are significantly associated with mortality in COPD patients3,4. We and others have also reported
that low-level pulmonary function, exercise tolerance (including 6-min walk distance and exercise-induced
desaturation), and BMI are correlated with a high frequency of e xacerbations5–8, indicating that evaluations of
exercise tolerance and body composition, in addition to pulmonary function, are important for predicting the
clinical course of COPD.
1
Division of Hematology, Respiratory Medicine and Oncology, Department of Internal Medicine, Faculty of
Medicine, Saga University, 5‑1‑1 Nabeshima, Saga, Saga Prefecture 849‑8501, Japan. 2Clinical Research Center,
Saga University Hospital, Saga, Japan. 3Advanced Comprehensive Functional Recovery Center, Saga University
Hospital, Saga, Japan. *email: si3222@cc.saga-u.ac.jp
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Clinical parameters
Age (years) 71.1 ± 9.0
Gender (male/female) 66/3
BMI (kg/m2) 21.4 ± 3.8
Smoking history (pack-year) 67.6 ± 33.0
GOLD stage (I/II/III/IV, n) 12/27/25/5
mMRC dyspnea scale (0/1/2/3/4, n) 5/18/27/16/3
COPD assessment test (n = 41) 16.8 ± 7.6
6-min walk distance (n = 48) (m) 386.1 ± 115.8
Medications
No respiratory medication, n (%) 5 (7.2%)
LAMA or LABA alone, n (%) 17 (24.6%)
LABA-LAMA combo, n (%) 19 (27.5%)
ICS-LABA combo, n (%) 9 (13.0%)
Triple combo, n (%) 19 (27.5%)
Pulmonary function
%VC (%) 100.4 ± 18.4
%FVC (%) 95.2 ± 17.5
FEV1 (L) 1.35 ± 0.59
FEV1/FVC (%) 43.8 ± 13.4
%FEV1 (%) 60.2 ± 24.2
DLco (%) 65.9 ± 24.3
Evaluation of skeletal muscle on CT (n = 56)
PMCSA (cm2) 25.9 ± 7.9
ECMCSA (cm2) 27.8 ± 6.2
Table 1. Demographics of the study participants (n = 69). BMI body mass index, GOLD global initiative
for chronic obstructive lung disease, mMRC modified medical research council, COPD chronic obstructive
pulmonary disease, LAMA long-acting muscarinic antagonist, LABA long acting β2 adrenergic agonist, ICS
inhaled corticosteroid, VC vital capacity, FVC forced vital capacity, FEV1 forced expiratory volume in 1 s, DLco
diffusing capacity of lung for carbon monoxide, PMCSA cross-sectional area of pectoralis muscles, ECMCSA
cross-sectional area of erector spinae muscles. Data are presented as mean ± standard deviation.
Decreasing exercise tolerance, normally measured by the 6-min walk test or cardiopulmonary exercise test-
ing (CPET), is one of the important clinical features related to a poor prognosis in COPD patients3,9,10, and with
CPET one can evaluate exercise tolerance with exertional ventilatory parameters precisely and s afely11,12. For
example, oxygen uptake ( V̇O2) at peak exercise, which represents exercise tolerance, is significantly correlated
with FEV1 and %FEV1 reflecting the severity of COPD13,14. Notably, with CPET, one can detect physical problems
including cardiac dysfunction and functional skeletal muscle disorders during the test, which contributes to
rapid initiation of t reatment15.
Weight loss is a common systemic characteristic of patients with COPD16, and skeletal muscle loss has greater
impact on the severity of COPD than decreased BMI17. Radiological analysis of skeletal muscles on computed
tomography (CT) is a useful procedure for quantitation without onerous physical i ntervention18,19, and the cross-
sectional area (CSA) of skeletal muscle on single-slice axial CT is significantly correlated with a poor prognosis
in COPD p atients20,21. In addition, the CSA of the erector spinae muscles (ECMs), which are anti-gravity mus-
cles, but not of the pectoralis muscles (PMs), is significantly associated with mortality in Japanese patients with
COPD21. Obviously, skeletal muscles are important for exercise tolerance, but the impact of exertional ventilatory
parameters on CPET compared to clinical parameters in patients with COPD is not fully understood.
The aim of the present study was to identify the correlations between exertional ventilatory parameters,
especially V̇O2 at peak exercise, and clinical parameters of COPD including skeletal muscle area. Our hypothesis
was that skeletal muscle areas are correlated with V̇O2 at peak exercise, and the correlation coefficient of ECMCSA
is higher than that of P MCSA.
Results
Parameters of cardiopulmonary exercise testing. In the present study, 69 COPD patients (66 males,
3 females) who underwent CPET were enrolled. The clinical baseline characteristics of the COPD patients are
shown in Table 1. V̇O2, which is a marker that reflects exercise t olerance22, was 295.6 ml/min at rest and 926.0 ml/
min at peak exercise. Body weight-adjusted V̇O2 was 5.3 ml/min/kg at rest and 16.2 ml/min/kg at peak exercise.
VT and VE were 773.2 ml and 12.9 l/min at rest and 1245.7 ml and 36.6 l/min at peak exercise, respectively. V̇Ė /V̇
22
CO2, which reflects pulmonary clearance of CO2 , was 49.3 at rest and 41.1 at peak exercise. VD/VT, which reflects
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At rest At peak exercise
Incremental load testing
V̇O2 (ml/min) 295.6 ± 68.2 926.0 ± 338.4
V̇O2 (ml/min/kg) 5.3 ± 1.2 16.2 ± 4.7
VT (ml) 773.2 ± 204.5 1245.7 ± 362.6
VE (L/min) 12.9 ± 2.6 36.6 ± 10.9
V̇E/V̇CO2 49.3 ± 8.9 41.1 ± 8.4
VD/VT 0.28 ± 0.07 0.26 ± 0.07
Breathing frequency (times/min) 17.7 ± 4.2 30.5 ± 8.1
Table 2. Results of cardiopulmonary exercise testing at rest and at peak exercise (n = 69). V̇ O2 oxygen uptake,
VT tidal volume, VE minute ventilation, V̇ E/V̇ CO2 ventilatory equivalent for carbon dioxide, VD/VT dead space to
tidal volume ratio. Data are presented as mean ± standard deviation.
V̇O2 (ml/min/kg)
at peak exercise
ρ p value
V̇E/V̇CO2 at rest − 0.46 < 0.0001
V̇E/V̇CO2 at peak exercise − 0.45 < 0.0001
VD/VT at rest − 0.36 0.002
VD/VT at peak exercise − 0.53 < 0.0001
Breathing frequency at rest − 0.35 0.003
Breathing frequency at peak exercise − 0.33 0.006
6-min walk distance (n = 48) 0.74 < 0.0001
Table 3. Correlation coefficients between V̇O2 at peak exercise and other CPET parameters and the 6-min
walk distance. V̇ O2 oxygen uptake, VT tidal volume, VE minute ventilation, V̇ E/V̇ CO2 ventilatory equivalent for
carbon dioxide, VD/VT dead space to tidal volume ratio.
the efficacy of pulmonary gas exchange, was 0.28 at rest and 0.26 at peak exercise. The respiratory rate was 17.7
breaths/min at rest and 30.5 breaths/min at peak exercise (Table 2).
Correlations between VO
˙ 2 (ml/min/kg) at peak exercise and other parameters on CPET and the
6‑min walk distance. Because V̇O2 (ml/min) is affected by body weight differences, V̇O2 adjusted by body
weight (ml/min/kg) at peak exercise is considered a precise marker for exercise t olerance22. Therefore, the evalu-
ation focused on that and its correlations with other CPET parameters and the 6-min walk distance. V̇O2 at peak
exercise was significantly correlated with V̇E/V̇CO2 at rest (ρ = − 0.46, p < 0.0001) and at peak exercise (ρ = − 0.45,
p < 0.0001), VD/VT at rest (ρ = − 0.36, p = 0.002) and at peak exercise (ρ = − 0.53, p < 0.0001), respiratory rate at
rest (ρ = − 0.35, p = 0.003) and at peak exercise (ρ = − 0.33, p = 0.006), and the 6-min walk distance (ρ = 0.74,
p < 0.0001) (Table 3, Supplementary Fig. S2a online). These data showed that V̇O2 (ml/min/kg) at peak exercise
reflected exercise tolerance in COPD patients.
Correlations between VO˙ 2 (ml/min/kg) at peak exercise and clinical parameters of COPD
including skeletal muscle area. To clarify the factors correlated with exercise tolerance as reflected by
V̇O2 (ml/min/kg) at peak exercise, correlation analysis between V̇O2 (ml/min/kg) at peak exercise and clinical
parameters of COPD including skeletal muscle area was performed. Age, BMI, %VC, %FVC, %FEV1, and diffus-
ing capacity of the lung for carbon monoxide (DLco) were not significantly correlated with V̇O2 at peak exercise.
The COPD assessment test score (ρ = − 0.35, p = 0.02, Supplementary Fig. S2b online) was weakly correlated with
V̇O2 at peak exercise. F EV1 (ρ = 0.39, p = 0.0009, Fig. 1a), FEV1/FVC (ρ = 0.33, p = 0.006, Fig. 1b), PMCSA (ρ = 0.36,
p = 0.007, Fig. 1c), and E
CMCSA (ρ = 0.39, p = 0.003, Fig. 1d) were significantly correlated with V̇O2 at peak exer-
cise (Table 4). Examining the difference in V̇O2 at peak exercise by COPD stage, COPD stage III and IV patients
had significantly lower levels of V̇O2 at peak exercise than stage II patients (Fig. 2a). In addition, examining the
difference in V̇O2 at peak exercise by the mMRC dyspnea scale score, patients with an mMRC scale score of 3
had a significantly lower V̇O2 at peak exercise than those with an mMRC scale score of 0 (Fig. 2b). For other
parameters on CPET, V̇E/V̇CO2 at peak exercise was significantly correlated with BMI (ρ = − 0.33, p = 0.007), the
COPD assessment test score (ρ = 0.58, p < 0.0001), DLco (ρ = − 0.42, p = 0.001), PMCSA (ρ = − 0.32, p = 0.02), and
ECMCSA (ρ = − 0.34, p = 0.01). In addition, V D/VT at peak exercise was significantly correlated with age (ρ = 0.34,
p = 0.005), BMI (ρ = − 0.28, p = 0.02), the COPD assessment test score (ρ = 0.41, p = 0.009), %VC (ρ = − 0.28,
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(a) (b)
30
30
ρ = 0.39
V’O2 (ml/min/kg) at peak exercise
V’O2 (ml/min/kg) at peak exercise
p = 0.0009 ρ = 0.33
25 25 p = 0.006
20 20
15 15
10 10
5
5
10 20 30 40 50 60 70 80
0 1 2 3
FEV1 (L) FEV1/FVC (%)
(c) (d)
30 30
V’O2 (ml/min/kg) at peak exercise
ρ = 0.36
V’O2 (ml/min/kg) at peak exercise
ρ = 0.39
p = 0.007 p = 0.003
25 25
20 20
15 15
10 10
5 5
0 20 40 60 10 20 30 40
PMCSA (cm2) ECMCSA (cm2)
Figure 1. Correlations between V̇O2 at peak exercise and clinical parameters of COPD. Correlations between
V̇O2 at peak exercise and (a) FEV1, (b) FEV1/FEV, (c) PMCSA, and (d) ECMCSA. V̇ O2 oxygen uptake, COPD
chronic obstructive pulmonary disease, FEV1 forced expiratory volume in 1 s, FVC forced vital capacity, PMCSA
cross-sectional area of the pectoralis muscles, ECMCSA cross-sectional area of the erector spinae muscles.
V̇O2 (ml/min/kg) at peak exercise
ρ p value
Age (years) − 0.22 0.08
BMI (kg/m2) 0.08 0.54
COPD assessment test − 0.35 0.02
%VC (%) 0.19 0.11
%FVC (%) 0.16 0.2
FEV1 (L) 0.39 0.0009
FEV1/FVC (%) 0.33 0.006
%FEV1 (%) 0.24 0.05
DLco (%) 0.26 0.05
PMCSA (cm2) 0.36 0.007
ECMCSA (cm2) 0.39 0.003
Table 4. Correlation coefficients between V̇O2 at peak exercise and clinical parameters of COPD including
skeletal muscle area. CPET Cardiopulmonary exercise testing, V̇ O2 oxygen uptake, BMI; body mass index,
COPD chronic obstructive pulmonary disease, VC vital capacity, FVC forced vital capacity, FEV1 forced
expiratory volume in 1 s, DLco diffusing capacity of lung for carbon monoxide, PMCSA cross-sectional area of
pectoralis muscles, ECMCSA cross-sectional area of erector spinae muscles.
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Figure 2. Results of V̇O2 by (a) GOLD stage and (b) mMRC dyspnea scale score. *p < 0.05. V̇ O2 oxygen uptake,
GOLD Global Initiative for Chronic Obstructive Lung Disease, mMRC modified Medical Research Council.
Multivariate analysis
β 95% CI p value
Age (years) − 0.059 − 0.185–0.068 0.36
FEV1 (L) 0.826 − 1.01–2.662 0.37
PMCSA (cm2) 0.175 0.03–0.319 0.02
Table 5. Multivariate analysis of correlations between V̇O2 at peak exercise and age, FEV1, and P
MCSA as
predictive variables. FEV1 forced expiratory volume in 1 s, ECMCSA cross-sectional area of erector spinae
muscles, β standardized β value, CI confidence interval.
Multivariate analysis
β 95% CI p value
Age (years) − 0.058 − 0.187–0.072 0.37
FEV1 (L) 0.785 − 1.099–2.668 0.41
ECMCSA (cm2) 0.192 − 0.001–0.385 0.052
Table 6. Multivariate analysis of correlations between V̇O2 at peak exercise and age, FEV1, and E
CMCSA
as predictive variables. FEV1 forced expiratory volume in 1 s, ECMCSA cross-sectional area of erector spinae
muscles, β standardized β value, CI confidence interval.
p = 0.02), FEV1 (ρ = -0.42, p = 0.004), FEV1/FVC (ρ = − 0.36, p = 0.003), %FEV1 (ρ = − 0.27, p = 0.03), PMCSA
(ρ = − 0.35, p = 0.008), and ECMCSA (ρ = − 0.38, p = 0.004) (Supplementary Table S1 online).
Multivariate analysis of the correlation between VO
˙ 2 at peak exercise and predictive variables
including age, FEV1, and skeletal muscle areas. To evaluate the impact of skeletal muscle areas on
exercise tolerance, multivariate analysis was performed using variables of age, FEV1 and skeletal muscle areas.
MCSA (β value [95% confidence interval] 0.175 [0.03–0.319], p = 0.02) was weakly correlated after adjustment
P
(Table 5). In addition, ECMCSA (0.192 [− 0.001–0.385] p = 0.052) tended to be correlated, but not significantly
after adjustment (Table 6).
Discussion
In the present cross-sectional study, correlations between exercise tolerance indicated by V̇O2 at peak exercise
and clinical parameters including skeletal muscle area were examined in Japanese patients with COPD. It was
confirmed that V̇O2 at peak exercise was significantly correlated with 6-min walk distance and other CPET
parameters, such as V̇E/V̇CO2, VD/VT, and respiratory rate, which suggested that V̇O2 at peak exercise is a useful
marker of exercise tolerance for COPD patients. The analysis of correlation coefficients showed that the COPD
assessment test, F
EV1, FEV1/FVC, PMCSA, and E CMCSA were significantly correlated with V̇O2 at peak exercise,
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even though the correlations were weak. Additionally, the correlation coefficient between V̇O2 at peak exercise
and ECMCSA are comparable to that between V̇O2 at peak exercise and P MCSA.
Loss of exercise tolerance is an important and widely recognized clinical manifestation of COPD15,22. With
respect to the mechanisms, exercise-induced dyspnea with dynamic pulmonary hyperinflation and desaturation
of oxygen, which is a representative manifestation of COPD, contributes to a low threshold of exhaustion with
the early appearance of anaerobic metabolites in skeletal muscles during exercise22. Thus, V̇O2 at peak exercise on
CPET, which is determined by cellular O2 demand and the maximal rate of O2 transport, is considered a useful
marker of exercise tolerance in COPD p atients15. Diaz et al. analyzed 52 patients with mild to severe COPD, and
air-flow limitation, which reflects the presence of dynamic hyperinflation, was found to be significantly associated
with V̇O2 at peak e xercise12. Moreover, Kagawa et al. analyzed 294 patients with COPD who underwent CPET,
and they found that decreased F EV1 was associated with a low V̇O2 at peak e xercise13. These reports showed that
limitation of exercise tolerance predicted by decreased V̇O2 at peak exercise is an important phenotype of COPD,
as shown in the present study (Table 4, Fig. 1a,b). The severity of COPD predicted by %FEV1 is also related to the
decrease of exercise tolerance, and Yamamoto et al. reported that V̇O2 at peak exercise was significantly higher
in COPD patients in GOLD stages I and II than in those in GOLD stages III and IV14. The current results also
showed that the level of V̇O2 at peak exercise tended to be decreased depending on the GOLD stage, except for
stage I (Fig. 2a), although the correlation between V̇O2 at peak exercise and %FEV1 was weak (Table 4). Notably,
V̇O2 at peak exercise in GOLD stage II patients was higher than that in GOLD stage I patients, as shown in Fig. 2a,
although the difference was not significant. As indicated in Fig. 1a, the level of V̇O2 at peak exercise has various
values in patients who showed a high FEV1, which might indicate that exercise tolerance in the early stage of
COPD involves factors except for airway limitation such as skeletal muscle mass.
Loss of skeletal muscles with bodyweight reduction, called sarcopenia, is also an important characteristic
of COPD patients20,23,24. Reduction of fat-free mass containing skeletal muscle is associated with mortality in
patients with C OPD25. In addition, a previous report showed that COPD patients with decreased skeletal muscles,
calculated by bioelectrical impedance analysis, walked a significantly shorter distance on the incremental shuttle
walk test, which is another index of exercise tolerance, than those with preserved skeletal muscles26. With respect
to the mechanisms, loss of skeletal muscles causes increased O2 demand as exercise intensity increases and earlier
reaching of the anaerobic threshold with metabolic acidosis and increased lactate, which limits exercise tolerance
in patients with C OPD27,28. The present study showed that skeletal muscle area, including P MCSA and E CMCSA,
was significantly correlated with V̇O2 at peak exercise, which is consistent with these data (Table 4, Fig. 1c,d).
Notably, other gas exchange parameters on CPET such as V̇E/V̇CO2 and VD/VT at peak exercise were associ-
ated with the clinical data of COPD, including skeletal muscle area (Supplementary Table S1 online). These
parameters were reported to be significantly higher in patients with COPD than in healthy i ndividuals29, and V̇
E/V̇CO2, which reflects decreased pulmonary clearance of CO2 during exercise, was correlated with BMI, %FEV1,
and DLco, in addition to skeletal muscle area. Moreover, V D/VT, which reflects worse pulmonary gas exchange
efficacy, was correlated with age, BMI, %VC, F EV1, FEV1/FVC, and %FEV1, in addition to skeletal muscle area.
Interestingly, the COPD assessment test score was strongly correlated with these parameters, suggesting that V̇
E/V̇CO2 and VD/V T might reflect COPD-related symptoms (Supplementary Table S1 online).
The present study has several limitations. First, correlations with physical activity were not evaluated. Sec-
ond, correlations were evaluated using clinical parameters of COPD and skeletal muscle area, which acted as
confounding factors. Third, study participants were selected by physicians’ suggestions and patients’ acceptance,
which might have caused selection bias. Fourth, it is unclear that the current results for the correlation between
exercise tolerance and skeletal muscle area is specific for patients with COPD, because healthy controls were not
included. Fifth, the present study involved patients at a single hospital with limited ethnic diversity and a small
sample size. Additionally, the percentage of females was extremely low in the present study, consistent with the
general population of COPD, which might affect generalizability. To confirm the validity of the present results,
multicenter, prospective studies with a larger number of patients should be performed.
Conclusions
The present cross-sectional study showed that in FEV1, FEV1/FVC, and skeletal muscle areas including PMCSA
and ECMCSA are significantly correlated with exercise tolerance, even though the correlations are weak. These data
suggest that pulmonary function and skeletal muscles contribute to exercise tolerance in patients with COPD.
Methods
Study design. The cross-sectional study was designed following the recommendations of the STROBE
statement and approved by the ethics committee of Saga University Hospital (approval number: 2020-11-R-03,
approval date: Jan 27, 2021) in accordance with the 1964 Declaration of Helsinki. Informed consent of the par-
ticipants was obtained in the form of opt-out on the website. Those who rejected were excluded.
Patients and setting. The medical records of 69 patients diagnosed with COPD who underwent CPET at
the Saga University Hospital between 2009 and 2020 were included in the present study. All patients satisfied
the definition criteria of the Global Initiative for Chronic Obstructive Lung Disease (GOLD). Briefly, patients
were confirmed to have FEV1/FEV < 0.7 after using a bronchodilator, a smoking index > 10 pack years, and symp-
toms including chronic cough, sputum, and dyspnea. Patients with either a current or a previous diagnosis of
asthma were excluded. For patient information, age at the time CPET was performed was used, and clinical
parameters including BMI, modified Medical Research Council (mMRC) dyspnea scale, COPD assessment test,
6-min walk test, medication record, and pulmonary function at the time closest to when CPET was performed
(within ± 3 months) were evaluated. Thus, 41 patients who underwent the COPD assessment test and 48 patients
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who underwent the 6-min walk test were analyzed. Medications were selected at each physician’s discretion.
For handling of missing values, the participant data record was excluded for waves of data collection with miss-
ing values. The primary outcome was set as a significant correlation between V̇O2 at peak exercise and skeletal
muscle areas including PMCSA and ECMCSA. For sample size calculation, the correlation between V̇O2 at peak
exercise and skeletal muscle area have not been assessed, to the best of our knowledge, which suggests that the
accurate calculation was not feasible. However, previous studies reported that F EV1 was significantly correlated
with V̇O2 at peak exercise 14 and skeletal muscle area20. We hypothesized a significant correlation between V̇O2
at peak exercise and skeletal muscle area as with F EV1 (r = 0.4) and performed test of no correlation with two-
sided 0.05 of significant level and 0.8 of statistical power, which estimated a sample size of 47 patients. Thus, we
considered the current sample size of 69 patients was sufficient to achieve this primary outcome.
Cardiopulmonary exercise testing. A symptom-limited cycle ergometer (Strength Ergo 8, Mitsubishi
Electric Engineering, Japan) was used for CPET. Each patient wore a mask, and breath was analyzed using a gas
analyzer (Cpex-1, Inter Reha; Japan); V̇O2, expiratory tidal volume ( VT), minute ventilation (VE), ventilatory
equivalent for carbon dioxide (V̇E/V̇CO2), dead space to tidal volume ratio (VD/VT), and breathing frequency
at rest and at peak exercise were evaluated. Oxygen saturation, blood pressure, and the electrocardiogram were
measured during the test. In the exercise protocol, pre-exercise resting measurements were obtained within the
steady state period for more than 3 min. Incremental testing was then started by increasing the load by 10 W
per minute with a ramp-exercise protocol. The examination was continued until exhaustion or the predicted
maximum heart rate or blood pressure was surpassed, and showing electrocardiographic changes such as ST
segment depression of greater than 2 mm and a short run of premature ventricular contractions. Dyspnea inten-
sity was evaluated by a 10-point modified Borg category-ratio scale at rest and every 1 min after initiation of
the incremental load test. The data generated were measured breath-by-breath and as 30-s averages at rest and
during exercise.
CT scan acquisition and analysis. Chest CT for analysis of the pectoralis and erector spinae muscles that
was performed most closely to the time of CPET (within ± 3 years) was also selected; the average time between
CPET and chest CT was 198 days. Consequently, 56 patients were examined. For quantitative analysis, the CSAs
of the pectoralis muscles (PMCSA) and the erector spinae muscles (ESMCSA) were evaluated referring to the previ-
ously described method20,24,30. Briefly, left and right areas of the PMCSA identified by the superior aspect of the
aortic arch and the ESMCSA identified by the lower aspect of the 12th thoracic vertebrae on CT imaging recon-
structed using the mediastinal setting were identified and shaded manually. Finally, the sum of the left and right
muscle areas was examined. The measurements were performed by two pulmonary physicians independently
referring to the representative images (Supplemental Fig. S1a,b online), and average values were used.
Statistical analysis. For correlation analysis, Spearman’s rank correlation coefficients between exercise tol-
erance parameters such as V̇O2, V̇E/V̇CO2, VD/VT, breathing frequency, and 6-min walk distance, and clinical
parameters including age, BMI, COPD assessment test score, %VC, %FVC, FEV1, FEV1/FVC, %FEV1, DLco,
PMCSA, and E CMCSA were calculated to determine whether they were zero. Differences of V̇O2 at peak exercise
depending on GOLD stages and the mMRC dyspnea scale were analyzed by the Steel–Dwass method. Multivari-
ate analysis with linear regression analysis was performed for continuous variables, and β coefficient values were
calculated. Quantitative data are presented as means ± standard deviation (SD); significance was considered a p
value less than 0.05. Statistical analysis was performed with JMP Pro version 14.2.0 software (SAS Institute Inc.,
Cary, NC, USA).
Data availability
The datasets used and analyzed during the present study are available from the corresponding author on reason-
able request.
Received: 3 February 2021; Accepted: 26 July 2021
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Author contributions
H.T., K.T., and M.T. conceived and designed the project. H.T., Y.K., H.N., and H.I. analyzed and interpreted the
data. R.T. and A.T. advised on the statistical analysis. H.T., K.T., and H.S. prepared the manuscript with input
from all other authors. S.K. and N.A. checked the prepared manuscript. All authors reviewed the manuscript.
Competing interests
The authors declare no competing interests.
Additional information
Supplementary Information The online version contains supplementary material available at https://doi.org/
10.1038/s41598-021-95413-9.
Correspondence and requests for materials should be addressed to H.T.
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